Table of Content

Open Access iconOpen Access

ARTICLE

crossmark

PREDICTING THE WAX DEPOSITION RATE BASED ON EXTREME LEARNING MACHINE

Qi Zhuanga,* , Zhuo Chenb, Dong Liuc, Yangyang Tiand

a The Second Gas Production Plant, PetroChina Changqing Oilfield Company, Xi’an China
b Sinopec Northwest Oil field Company, Urumqi, China
c Safety and Environmental Supervision Department, PetroChina Changqing Oilfield Company, Xi’an China
d Shaanxi Key Laboratory of Advanced Stimulation Technology for Oil & Gas Reservoirs, College of Petroleum Engineering, Xi’an Shiyou University, Xi’an China
* Corresponding Author. E-mail: 1900679914@qq.com.

Frontiers in Heat and Mass Transfer 2022, 19, 1-8. https://doi.org/10.5098/hmt.19.19

Abstract

In order to improve the accuracy and efficiency of wax deposition rate prediction of waxy crude oil in pipeline transportation, A GRA-IPSO-ELM model was established to predict wax deposition rate. Using Grey Relational Analysis (GRA) to calculate the correlation degree between various factors and wax deposition rate, determine the input variables of the prediction model, and establish the Extreme Learning Machine (ELM) prediction model, improved particle swarm optimization (IPSO) is used to optimize the parameters of ELM model. Taking the experimental data of wax deposition in Huachi operation area as an example, the prediction performance of the model is evaluated by modeling and simulation, and compared with other models. The results show that the Mean Relative Error (MRE) and the Root Mean Square Error (RMSE) of the GRA-IPSO-ELM model are 0.351% and 0.049 respectively. Compared with other models, the GRA-IPSO-ELM model has better prediction performance.

Keywords


Cite This Article

APA Style
Zhuang, Q., Chen, Z., Liu, D., Tian, Y. (2022). PREDICTING THE WAX DEPOSITION RATE BASED ON EXTREME LEARNING MACHINE. Frontiers in Heat and Mass Transfer, 19(1), 1-8. https://doi.org/10.5098/hmt.19.19
Vancouver Style
Zhuang Q, Chen Z, Liu D, Tian Y. PREDICTING THE WAX DEPOSITION RATE BASED ON EXTREME LEARNING MACHINE. Front Heat Mass Transf. 2022;19(1):1-8 https://doi.org/10.5098/hmt.19.19
IEEE Style
Q. Zhuang, Z. Chen, D. Liu, and Y. Tian, “PREDICTING THE WAX DEPOSITION RATE BASED ON EXTREME LEARNING MACHINE,” Front. Heat Mass Transf., vol. 19, no. 1, pp. 1-8, 2022. https://doi.org/10.5098/hmt.19.19



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 597

    View

  • 402

    Download

  • 0

    Like

Related articles

Share Link